An effort to study the influence of tides on the longitudinal variation of vertical E×B drift over the African sector

Meteorological processes such as tides influence ionospheric variability through vertical coupling. For the first time, we have used data from Communication Navigation Outage and Forecasting System (C/NOFS) satellite from 2008–2015 to develop a Neural Network (NN) vertical E×B drift model over the African region, with inclusion of a proxy of tides as one of the inputs together with other physical and geophysical inputs. Two models (with and without tidal proxy input) were developed for both East and West African sectors. To derive the tidal proxy, we first calculate the 60-day running means per year which were subtracted from the actual vertical E×B drift measurements to obtain a set of residuals. The purpose of the subtraction was to remove long-term trends in vertical E×B drift that could potentially alias into tides. A Fast Fourier Transform (FFT) was then performed on the residuals per day to obtain amplitudes and phases which were used as tidal proxy representation in vertical E×B drift modelling. The developed model with tides’ proxy input showed an improvement of 22.2% and 16.7% over the East (38.8oE) and West (9.2oW) African sectors respectively. In most cases, the developed models were able to capture the diurnal patterns of vertical E×B drift including the expected pre-reversal enhancement. The performance of the two models during geomagnetically quiet days and storm periods was comparable but not similar.